FIZ Karlsruhe - Leibniz Institute for Information Infrastructure is one of the leading providers of scientific information and services and a member of the Leibniz Association. Our core tasks are the professional provision of research and patent information to science and industry as well as the development of innovative information infrastructures, e.g., with a focus on research data management, knowledge graphs and digital platforms. To this end, we conduct our own research, cooperate with renowned universities and research societies, and are internationally and interdisciplinarily networked. FIZ Karlsruhe is a limited liability company with a non-profit character and one of the largest non-university institutions of its kind.
Information Service Engineering (ISE) at FIZ Karlsruhe investigates models and methods for efficient semantic indexing, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination with symbolic logic are applied. ISE research relies and extends on knowledge representation standards developed for the Semantic Web. ISE research application areas include but are not limited to solutions for knowledge extraction, semantic annotation, semantic and exploratory search, as well as recommender systems and question answering. Besides basic methodological research, domains of applied ISE research are, amongst others, cultural heritage, digital humanities, materials science, and research data management.
We are looking for an ambitious person who aims for a successful scientific career in the context of knowledge graph related technologies contributing to the strategic research and technology goals of FIZ Karlsruhe
The offered position will be in the FIZ ISE research team
We are expecting innovative research on FIZ ISE research topics including active involvement in scientific publications, third party funding proposals, as well as in professional academic activities
Furthermore, supervision of master and bachelor theses as well as co-supervision of FIZ ISE PhD students is expected
We offer a productive and continuously evolving research environment and will actively support you in your further scientific qualification
Our goal is to perform internationally leading research which can be applied in high impact use cases
Qualifications and Skills:
An excellent completed PhD degree in Computer Science or a related field
Publications of research results in renowned, peer-reviewed journals and conferences
Proven software engineering skills and the ability to develop mature software components beyond pure research prototypes
Successful supervision of bachelor and master theses
Successful collaborations with other research groups, industry, as well as open-source and community-initiatives, for example in the context of publicly funded collaborative research projects
Experience in applying for funding from national, European and international funding agencies
Excellent English skills, written and spoken, German language skills are highly beneficial
Expertise in several of the following fields of research:
Knowledge Graphs and Semantic Web Technologies
Machine Learning and Deep Learning
Ontology Design and Ontological Engineering
Natural Language Processing
The candidate should be highly self-motivated, interested in tackling challenging research problems, have excellent organizational skills, be open minded, and have scientific leadership potential.
Why FIZ Karlsruhe:
Remuneration according to the German Collective Agreement for the Public Sector (TVöD VKA) including a company pension plan with VBL
Collaboration in a highly dynamic scientific and technical environment
Performance-oriented career and development opportunities
Flexible working time models and mobile working
Certified by the audit berufundfamilie, which guarantees the work-life balance of family and job
Company bike leasing option
The employment relationship is initially limited to two years, although our goal is a long-term cooperation. Applications from severely handicapped persons will be considered with preference, provided they are equally qualified. Information on data protection for employment advertisements can be found here.
If you have any technical questions, please contact Prof. Dr. Harald Sack (harald.sack [at] fiz-karlsruhe.de). Questions regarding the application process should be directed to Mr. Rainer Kurz (rainer.kurz [at] fiz-karlsruhe.de).
Excellent candidates are invited to apply with the following documents:
detailed curriculum vitae
copies of certificates and transcripts, if applicable
complete list of publications
letters of recommendation (at least two)
letter of motivation and research concept
Please send your complete application documents by e-mail, quoting the reference number 41/2022, to bewerbung [at] fiz-karlsruhe.de.